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On the reduction of the nearest-neighbor variation for more accurate classification and error estimates

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1 Author(s)
A. Djouadi ; Lucent Technol., Columbus, OH, USA

In designing the nearest-neighbor (NN) classifier, a method is presented to produce a finite sample size risk close to the asymptotic one. It is based on an attempt to eliminate the first-order effects of the sample size, as well as all higher odd terms. This method uses the 2-NN rule without the rejection option and utilizes a polarization scheme. Simulation results are included as a means of verifying this analysis

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:20 ,  Issue: 5 )